Increasing extreme rainfall and increasingly severe flood disasters worldwide make it essential to enhance flood resilience research and practice. The Sponge City Approach (SCA) has been proposed as a nature-based solution for solving pressing water problems in cities, but there is an urgent need to apply the approach at the broader catchment scale to address the rising challenges driven by climate change. This study established a Sponge Watershed Approach (SWA) using the “Source-Flow-Sink” framework and applied it in the Sishui River Basin in Zhengzhou, China, to reconstruct a town after a heavy rainfall disaster and enhance its resilience to future floods. An integrated modeling approach utilizing hydrologic, hydraulic, and flood-loss curve models was used to analyze and evaluate the flood-reduction effects of different strategies under multiple scenarios. The results show that: (1) a strategy focusing solely on interventions at the source of runoff cannot adequately cope with extreme rainfall, and a whole-system approach to managing floods is necessary instead; (2) the effectiveness of the flow strategy depends on the intervention magnitude and the location where interventions are made; (3) the sink strategy offers the most effective way (approximately 30% decrease in flood loss) to adapt to extreme rainfall; (4) the risk and impact of flood disaster in the town was significantly reduced with the SWA (approximately 35–50% decrease in flood loss) compared to those without any interventions; (5) the effects of these strategies are interactive, and the optimal strategy depends on the rainfall condition. These results demonstrate the practicability of SWA by integrating the source, flow, and sink strategy at the whole-catchment scale, which will help promote natural flood management and enhance the climate resilience of catchments worldwide.

Urban noise causes a variety of health problems, and its prevention and control have thus become an important research topic in urban governance. Although existing literature is fairly comprehensive in revealing the physical noise patterns, it lacks the concern of people’s perceived seriousness, especially at the macroscopic, i.e., citywide scale. In this paper, we borrow from the “exposure-perception-behavior” theory in environmental psychology, and propose an analytical framework for diagnosing the urban noise problem that integrates the Infrastructural and Social Sensing perspectives. Utilizing noise monitoring data that fills the spatiotemporal granularity gaps of official noise monitoring, as well as the “12345” urban complaint hotline records which serve as a proxy for residents’ perceived noise levels, we empirically examine the mechanisms for physical magnitude and perceived seriousness of urban noise, respectively, by taking the Jiangbei District of Ningbo City, China as an example. Results show that the existence of perceptual bias and behavioral preference effects did shape people’s perceived noise problem map that is vastly different from that of the physical noise magnitude, in which the semantics of urban places, temporal rhythms of life, and population demographics significantly influenced people’s tolerance of noise. We conclude the paper with suggestions on updating the existing National Standard for urban noise regulation to reflect the perceptual aspect, and also methodological discussions on possible ways to recognize and utilize the perceptual bias in social-sensing big-data to better accommodate urban governance.